Christophe Blefari

JANUARY 20, 2024

Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. In order to understand today's data engineering I think that this is important to at least know Hadoop concepts and context and computer science basics.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Booking.com Engineering

DECEMBER 2, 2022

BigQuery saves us substantial time — instead of waiting for hours in Hive/Hadoop, our median query run time is 20 seconds for batch, and 2 seconds for interactive queries[3]. Managing Workflows Data, delivered with quality at the required moment, is at the heart of our system performance.

Systems 52

Systems Cloud MySQL Relational Database 52

LinkedIn Engineering

DECEMBER 19, 2023

Co-authors: Arjun Mohnot , Jenchang Ho , Anthony Quigley , Xing Lin , Anil Alluri , Michael Kuchenbecker LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. Historically, deploying code changes to Hadoop big data clusters has been complex.

Big Data 92

Big Data Hadoop Metadata Data 92

Cloudera

MAY 18, 2021

Prior the introduction of CDP Public Cloud, many organizations that wanted to leverage CDH, HDP or any other on-prem Hadoop runtime in the public cloud had to deploy the platform in a lift-and-shift fashion, commonly known as “Hadoop-on-IaaS” or simply the IaaS model. Introduction.

Hadoop 85

Hadoop Cloud AWS Utilities 85

Data Engineering Podcast

MARCH 27, 2022

You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms. How have the design and goals of the system changed or evolved since you started working on it? Can you explain how the Privacera platform is architected?

Data Governance 130

Data Governance Government Cloud Building 130

Cloudera

AUGUST 26, 2021

Ozone natively provides Amazon S3 and Hadoop Filesystem compatible endpoints in addition to its own native object store API endpoint and is designed to work seamlessly with enterprise scale data warehousing, machine learning and streaming workloads. Data ingestion through ‘s3’. As described above, Ozone introduces volumes to the world of S3.

Data Science 111

Data Science Cloud Hadoop Metadata 111

Data Engineering Podcast

MAY 18, 2021

Summary Data lineage is the common thread that ties together all of your data pipelines, workflows, and systems. In order to eliminate the wasted effort of building custom integrations every time you want to combine lineage information across systems Julien Le Dem introduced the OpenLineage specification.

Metadata 100

Metadata Kafka Data Warehouse Hadoop 100

ProjectPro

JUNE 22, 2017

What is a Hadoop Cluster? In general, a computer cluster is a collection of various computers that work collectively as a single system. “A hadoop cluster is a collection of independent components connected through a dedicated network to work as a single centralized data processing resource.

Hadoop 52

Hadoop IT Data Analysis Big Data 52

ProjectPro

JANUARY 12, 2016

Choosing the right Hadoop Distribution for your enterprise is a very important decision, whether you have been using Hadoop for a while or you are a newbie to the framework. Different Classes of Users who require Hadoop- Professionals who are learning Hadoop might need a temporary Hadoop deployment.

Hadoop 52

Hadoop Big Data Metadata Java 52

ProjectPro

JANUARY 31, 2023

Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS. RDBMS is a part of system software used to create and manage databases based on the relational model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JUNE 14, 2017

Hadoop was first made publicly available as an open source in 2011, since then it has undergone major changes in three different versions. Apache Hadoop 3 is round the corner with members of the Hadoop community at Apache Software Foundation still testing it. The major release of Hadoop 3.x x vs. Hadoop 3.x

Hadoop 52

Hadoop Java Big Data Coding 52

ProjectPro

NOVEMBER 6, 2015

Hadoop has continued to grow and develop ever since it was introduced in the market 10 years ago. Every new release and abstraction on Hadoop is used to improve one or the other drawback in data processing, storage and analysis. Apache Hive is an abstraction on Hadoop MapReduce and has its own SQL like language HiveQL.

Hadoop 52

Hadoop SQL Java Metadata 52

Data Engineering Weekly

DECEMBER 29, 2022

Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. There are not many sources to pull the metadata. The modern(?)

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Cloudera

OCTOBER 15, 2021

Apache Ozone has added a new feature called File System Optimization (“FSO”) in HDDS-2939. The FSO feature provides file system semantics (hierarchical namespace) efficiently while retaining the inherent scalability of an object store. We enabled Apache Ozone’s FSO feature for the benchmarking tests.

Cloud 87

Cloud Hadoop Data Analytics Metadata 87

Data Engineering Podcast

DECEMBER 16, 2019

The solution to discoverability and tracking of data lineage is to incorporate a metadata repository into your data platform. The metadata repository serves as a data catalog and a means of reporting on the health and status of your datasets when it is properly integrated into the rest of your tools.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

AltexSoft

JULY 18, 2023

Spark SQL, a component of Apache Spark, enables in-depth analysis across large datasets stored in distributed systems, thereby providing insights to drive business decisions. Companies employ Spark for customer churn prediction , fraud detection , and recommender systems. Data analysis. Stream processing. Directed Acyclic Graph (DAG).

Big Data 52

Big Data Data Process Process Hadoop 52

ProjectPro

FEBRUARY 18, 2016

With big data seeping into every facet of our lives, we are trying to build robust systems which can process petabytes of data in a fast and accurate manner. Apache Hadoop, an open source framework is used widely for processing gigantic amounts of unstructured data on commodity hardware. Table of Contents What is Apache Zookeeper?

Hadoop 40

Hadoop Management Metadata Java 40

ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40

Data Engineering Podcast

MARCH 22, 2021

For analytical systems, the only way to provide this reliably is by implementing change data capture (CDC). Unfortunately, this is a non-trivial undertaking, particularly for teams that don’t have extensive experience working with streaming data and complex distributed systems. What are the alternatives to CDC?

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

Data Engineering Weekly

JUNE 29, 2023

Databricks and Snowflake are better places to index the data and its metadata to enable natural language query capabilities. The question remains how far the data catalog tools can go with just the metadata. It significantly increases the friction in integrating this system, which soon becomes a nightmare.

Data Engineering 76

Data Engineering Data Engineer Google Cloud Engineering 76

ProjectPro

MAY 1, 2018

News on Hadoop - April 2018 Big Data and Cambridge Analytica: 5 Big Picture Truths.Datamation.com, April 2, 2018. where plain Hadoop was at 1.0 Source -[link] ) Africa has the potential to be a leader in open source distributed computing, says Standard Bank Hadoop expert.Computing.co.uk, April 26, 2018.

Hadoop 40

Hadoop Banking Healthcare Food 40

Cloudera

APRIL 22, 2021

on Cisco UCS S3260 M5 Rack Server with Apache Ozone as the distributed file system for CDP. Collects and aggregates metadata from components and present cluster state. Metadata in cluster is disjoint across components. Cloudera has partnered with Cisco in helping build the Cisco Validated design (CVD) for Apache Ozone.

Pipeline-centric 100

Pipeline-centric Data Lake Hadoop Metadata 100

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

APRIL 20, 2017

You have read some of the best Hadoop books , taken online hadoop training and done thorough research on Hadoop developer job responsibilities – and at long last, you are all set to get real-life work experience as a Hadoop Developer.

Hadoop 40

Hadoop Big Data Coding Project 40

Cloudera

NOVEMBER 8, 2022

Ozone is also highly available — the Ozone metadata is replicated by Apache Ratis, an implementation of the Raft consensus algorithm for high-performance replication. Since Ozone supports both Hadoop FileSystem interface and Amazon S3 interface, frameworks like Apache Spark, YARN, Hive, and Impala can automatically use Ozone to store data.

Metadata 82

Metadata Algorithm Hadoop Cloud 82

Data Engineering Podcast

OCTOBER 14, 2018

Summary With the growth of the Hadoop ecosystem came a proliferation of implementations for the Hive table format. Unfortunately, with no formal specification, each project works slightly different which increases the difficulty of integration across systems.

Data Lake 100

Data Lake Big Data Cloud Hadoop 100

Cloudera

AUGUST 10, 2021

Apache Ozone enhancements deliver full High Availability providing customers with enterprise-grade object storage and compatibility with Hadoop Compatible File System and S3 API. . The Atlas – Kafka integration is provided by the Atlas Hook that collects metadata from Kafka and stores it in Atlas.

Cloud 97

Cloud Kafka Metadata SQL 97

Cloudera

MARCH 9, 2021

While Cloudera Data Platform (CDP) already supports the entire data lifecycle from ‘Edge to AI’, we at Cloudera are fully aware that enterprises have more systems outside of CDP. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 95

Data Governance Government Metadata Datasets 95

Ascend.io

APRIL 19, 2023

Previous eras of data infrastructure, such as Teradata and Informatica, gave way to “big data” platforms like Hadoop and Spark, which initially catered to infrastructure experts rather than a broader audience. The modern data stack emerged as a response to a glaring gap in the data ecosystem: a dearth of developer tools.

Metadata 52

Metadata Business Analyst Hadoop Software Engineer 52

ProjectPro

MARCH 23, 2015

In one of our previous articles we had discussed about Hadoop 2.0 YARN framework and how the responsibility of managing the Hadoop cluster is shifting from MapReduce towards YARN. In one of our previous articles we had discussed about Hadoop 2.0 Here we will highlight the feature - high availability in Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Metadata 40

Data Engineering Podcast

JUNE 8, 2021

Summary The way to build maintainable software and systems is through composition of individual pieces. One such component that has gone above and beyond its originally envisioned use case is BookKeeper, a distributed storage system that is optimized for durability and speed.

Data Warehouse 100

Data Warehouse Hadoop Metadata Architecture 100

ProjectPro

OCTOBER 31, 2016

Having complete diverse big data hadoop projects at ProjectPro, most of the students often have these questions in mind – “How to prepare for a Hadoop job interview?” ” “Where can I find real-time or scenario-based hadoop interview questions and answers for experienced?” were excluded.).

Hadoop 52

Hadoop Big Data Utilities NoSQL 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.); Problem-solving skills.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

APRIL 11, 2016

Let’s face it; the Hadoop Interview process is a tough cookie to crumble. If you are planning to pursue a job in the big data domain as a Hadoop developer , you should be prepared for both open-ended interview questions and unique technical hadoop interview questions asked by the hiring managers at top tech firms.

Hadoop 40

Hadoop Big Data Java Unstructured Data 40

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

Data Engineering Podcast

FEBRUARY 13, 2022

You can observe your pipelines with built in metadata search and column level lineage. What other tools/systems might you replace with Rudderstack? You can observe your pipelines with built in metadata search and column level lineage. What other tools/systems might you replace with Rudderstack?

Building 100

Building Hadoop Data Pipeline Metadata 100

Data Engineering Weekly

FEBRUARY 18, 2024

One can’t deny the role of Redshift in bringing the cloud data warehouse to the masses, starting the end of the Big Data era with Hadoop. I believe the data ownership problem is much deeper than simple metadata management. All the retrospect keeps me wondering, So What is Next? What are we stepping into?

Data Engineering 62

Data Engineering Data Engineer Engineering Data 62